Prof. Dr. Frederick Klauschen
Prof. Dr. Frederick Klauschen
Research Group Lead / Charité
Research Grouplead | BIFOLD
Director | Pathologisches Institut, Ludwig-Maximilian-Universität München
Group Leader
Institute of Pathology
Charité UNIVERSITÄTSMEDIZIN BERLIN
| 2012 | Novartis Pathology-Oncology Award |
| 2011 | Human Frontier Science Program Young Investigator Award |
| 2004 | NIH Postdoctoral Fellowship Award |
Systems biological integration of proteogenomic profiles and histological images through bioinformatics and machine learning with the goal to better understand and predict pathological mechanisms in tumors and finally, to better diagnose and treat cancer.
- German Pathological Society
- International Academy of Pathology
- German Physical Society
Simon Schallenberg, Gabriel Dernbach, Sharon Ruane, Philipp Jurmeister, Cornelius Böhm, Kai Standvoss, Sandip Ghosh, Marco Frentsch, Mihnea P. Dragomir, Philipp G. Keyl, Corinna Friedrich, Il-Kang Na, Sabine Merkelbach-Bruse, Alexander Quaas, Nikolaj Frost, Kyrill Boschung, Winfried Randerath, Georg Schlachtenberger, Matthias Heldwein, Ulrich Keilholz, Khosro Hekmat, Jens-Carsten Rückert, Reinhard Büttner, Angela Vasaturo, David Horst, Lukas Ruff, Maximilian Alber, Klaus-Robert Müller, Frederick Klauschen
AI-powered spatial cell phenomics enhances risk stratification in non-small cell lung cancer
Philipp Keyl, Julius Keyl, Andreas Mock, Gabriel Dernbach, Liliana H Mochmann, Niklas Kiermeyer, Philipp Jurmeister, Michael Bockmayr, Roland F Schwarz, Grégoire Montavon, Klaus-Robert Müller, Frederick Klauschen
Neural interaction explainable AI predicts drug response across cancers
Jonah Kömen, Edwin D. de Jong, Julius Hense, Hannah Marienwald, Jonas Dippel, Philip Naumann, Eric Marcus, Lukas Ruff, Maximilian Alber, Jonas Teuwen, Frederick Klauschen, Klaus-Robert Müller
Towards Robust Foundation Models for Digital Pathology
Tabael L. Turan, Amrei Dilling, Frederick Klauschen, Insaf Haoues, Rose K. C. Moritz, Thomas K. Eigentler, Kamran Ghoreschi, Ulrike Blume-Peytavi
Carcinoma en Cuirasse Revealing Urothelial Carcinoma Recurrence
Giulia Pesch, Ignazio Piseddu, Jan Gaertig, Nora Kramer, Rafaela Kramer, Thomas U. Schulz, Maximilian Zwiebel, Stephan Ledderose, Jimmy Retzlaff, Markus Eckstein, Georg Schett, Claudia Kammerbauer, Christina Schmitt, Joerg Kumbrink, Michael Erdmann, Wolfgang Kruis, Michael Dougan, Julia Mayerle, Lars E. French, Julio Vera, Thierry M. Nordmann, Matthias Mann, Frederick Klauschen, David Anz, Lucie Heinzerling
Deep Immune Phenotyping Reveals Distinct Immunopathogenesis in Checkpoint Inhibitor–Induced Colitis Compared with Ulcerative Colitis
AI Improves Lung Cancer Diagnostics
An interdisciplinary research team from BIFOLD (Berlin Institute for the Foundations of Learning and Data), Technische Universität Berlin, Universitätsklinikum Köln, Charité - Universitätsmedizin Berlin, the AI company Aignostics, and Ludwig Maximilians University Munich (LMU) has developed a novel AI-based method to more accurately predict the survival of lung cancer patients.
AI in medicine: new approach for more efficient diagnostics
Researchers from LMU, BIFOLD, and Charité have developed a new AI tool that uses imaging data to also detect less frequent diseases of the gastrointestinal tract. In contrast to conventional models, the new AI only needs training data from common findings to detect deviations.
AI facilitates breakthrough in cancer diagnostics
So-called sinonasal undifferentiated carcinomas (SNUCs) are extremely difficult to diagnose. An interdisciplinary team of researchers has developed an AI tool that reliably distinguishes tumors on the basis of chemical DNA modifications
An overview of the current state of research in BIFOLD
Since the official announcement of the Berlin Institute for the Foundations of Learning and Data in January 2020, BIFOLD researchers achieved a wide array of advancements in the domains of Machine Learning and Big Data Management as well as in a variety of application areas by developing new Systems and creating impactfull publications. The following summary provides an overview of recent research activities and successes.